SILC：一种新的基于方向小波的普朗克内线性组合CMB温度图
SILC: a new Planck Internal Linear Combination CMB temperature map using directional wavelets
摘要：
我们提出了新的干净的地图的CMB温度各向异性（普朗克测量）构造一种新的内部线性组合（ILC）算法，使用方向，尺度离散小波-尺度离散，方向小波ILC或SILC。方向小波与球面上的信号进行卷积，可以分离出CMB和前景所特有的各向异性结构。扩展以前的分量分离方法，使用前景的频率，空间和谐波特征将它们从宇宙背景信号中分离出来，SILC还可以使用前景和CMB中的形态信息来更好地定位清洁算法。我们测试普朗克数据和模拟的方法，证明与现有的组件分离算法的一致性，并讨论如何优化形态信息的使用，通过改变方向小波的数量作为空间尺度的函数。我们发现，结合使用的方向和轴对称小波尺度依赖于可以产生更高质量的CMB温度图。我们的研究结果设置阶段的SILC偏振各向异性通过扩展到自旋小波的应用。
英文摘要：
We present new clean maps of the CMB temperature anisotropies (as measured by Planck) constructed with a novel internal linear combination (ILC) algorithm using directional, scale-discretised wavelets --- Scale-discretised, directional wavelet ILC or SILC. Directional wavelets, when convolved with signals on the sphere, can separate the anisotropic filamentary structures which are characteristic of both the CMB and foregrounds. Extending previous component separation methods, which use the frequency, spatial and harmonic signatures of foregrounds to separate them from the cosmological background signal, SILC can additionally use morphological information in the foregrounds and CMB to better localise the cleaning algorithm. We test the method on Planck data and simulations, demonstrating consistency with existing component separation algorithms, and discuss how to optimise the use of morphological information by varying the number of directional wavelets as a function of spatial scale. We find that combining the use of directional and axisymmetric wavelets depending on scale could yield higher quality CMB temperature maps. Our results set the stage for the application of SILC to polarisation anisotropies through an extension to spin wavelets.
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